EAGER: Data Privacy for Smart Meter Data: A Scenario-Based Study

EAGER：智能电表数据的数据隐私：基于场景的研究

• 批准号: 1447589
• 负责人: Jason Dedrick
• 金额: $ 26.61万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1447589&HistoricalAwards=false
• 关键词: EAGER; Data; Privacy; Smart; Meter

Smart electric meters comprise one key technology element in an overall strategy to modernize the nation's energy infrastructure. Smart meters capture data on household energy usage at frequent intervals and transmit those data to utility companies, who use the data to automate meter reading and billing, detect and respond to outages, and manage grid operations. Data collected over time can be used to forecast demand, understand customer behavior and develop new service and pricing plans. In the long run, these data can drive forecasting and control models that allow utilities to respond rapidly to fluctuations in power demand with compensatory load control strategies. This capability can reduce the magnitude of peak demand, thereby reducing both infrastructure costs and the consumption of fossil fuels that power peak generation facilities. Despite these advantages, smart meter data also appear to create powerful customer privacy concerns that may inhibit the adoption of smart meter technology by utilities. To address privacy concerns pertaining to the smart meter data, this project proposes three studies: Study 1 uses public data on electricity usage to develop a set of privacy scenarios that will be tested in focus groups to explore consumer privacy concerns. Study 2 involves a quasi-experiment to assess key dimensions of the scenarios and help identify which scenario has the highest level of acceptability to consumers. Study 3 involves one-on-one discussions with utility company representatives to develop a toolbox of communication methods and content that balance consumers' privacy concerns with the goals and constraints of utilities. The current theoretical model of privacy and technology, based on an information boundary framework, posits that consumers' willingness to share private information is rooted in the nature of the relationship with the party with whom the information is shared. Although a number of researchers have applied this information boundary framework to intra-organizational situations, the framework has not been tested in the context of smart meter data privacy. In the proposed sequence of three studies, this project gathers data from informants with the intention of understanding whether the information boundary framework is applicable to examining the relationships between consumers and regulated monopolies. The proposed project provides insights into public attitudes and concerns, as well as industry practices and policies regarding privacy of smart meter data. Through direct interaction with utility companies, as well as dissemination at industry conferences, in trade journals and through the media, the researchers will share their findings with practitioners, regulators and others who can create solutions that give customers confidence about the protection of their data.

智能电表是国家能源基础设施现代化总体战略中的一个关键技术要素。智能电表以频繁的时间间隔捕获家庭能源使用数据，并将这些数据传输给公用事业公司，公用事业公司使用这些数据自动进行电表阅读和计费，检测和响应停电，并管理电网运营。随着时间的推移收集的数据可用于预测需求，了解客户行为并制定新的服务和定价计划。 从长远来看，这些数据可以驱动预测和控制模型，使公用事业公司能够通过补偿性负荷控制策略快速响应电力需求的波动。这种能力可以降低峰值需求的幅度，从而降低基础设施成本和为峰值发电设施供电的化石燃料的消耗。尽管有这些优点，智能电表数据似乎也会产生强大的客户隐私问题，这可能会抑制公用事业采用智能电表技术。为了解决与智能电表数据有关的隐私问题，该项目提出了三项研究：研究1使用关于电力使用的公共数据来开发一组隐私场景，这些场景将在焦点小组中进行测试，以探索消费者隐私问题。研究2涉及一个准实验，以评估场景的关键维度，并帮助确定哪种场景具有最高的消费者接受程度。研究3涉及与公用事业公司代表进行一对一的讨论，以开发一个沟通方法和内容的工具箱，平衡消费者的隐私问题与公用事业的目标和限制。目前的隐私和技术的理论模型，基于一个信息边界框架，假设消费者愿意分享私人信息是植根于与谁的信息共享的一方的关系的性质。虽然一些研究人员已经将此信息边界框架应用于组织内的情况，但该框架尚未在智能电表数据隐私的背景下进行测试。在三项研究的拟议序列中，本项目收集了来自知情人的数据，目的是了解信息边界框架是否适用于审查消费者和受管制垄断企业之间的关系。拟议项目提供了对公众态度和关注的见解，以及有关智能电表数据隐私的行业惯例和政策。通过与公用事业公司的直接互动，以及在行业会议、行业期刊和媒体上的传播，研究人员将与从业人员、监管机构和其他能够创建解决方案的人分享他们的发现，这些解决方案可以让客户对数据保护充满信心。